Estimation of colorectal adenoma recurrence with dependent censoring

Persistent Link:
http://hdl.handle.net/10150/610044
Title:
Estimation of colorectal adenoma recurrence with dependent censoring
Author:
Hsu, Chiu-Hsieh; Long, Qi; Alberts, David
Affiliation:
Division of Epidemiology and Biostatistics, College of Public Health, University of Arizona, Tucson, AZ, 85724, USA; Arizona Cancer Center, College of Medicine, University of Arizona, Tucson, AZ, 85724, USA; Department of Biostatistics and Bioinformatics, School of Public Health, Emory University, Atlanta, GA, 48109, USA
Issue Date:
2009
Publisher:
BioMed Central
Citation:
BMC Medical Research Methodology 2009, 9:66 doi:10.1186/1471-2288-9-66
Journal:
BMC Medical Research Methodology
Rights:
© 2009 Hsu et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0)
Collection Information:
This item is part of the UA Faculty Publications collection. For more information this item or other items in the UA Campus Repository, contact the University of Arizona Libraries at repository@u.library.arizona.edu.
Abstract:
BACKGROUND:Due to early colonoscopy for some participants, interval-censored observations can be introduced into the data of a colorectal polyp prevention trial. The censoring could be dependent of risk of recurrence if the reasons of having early colonoscopy are associated with recurrence. This can complicate estimation of the recurrence rate.METHODS:We propose to use midpoint imputation to convert interval-censored data problems to right censored data problems. To adjust for potential dependent censoring, we use information from auxiliary variables to define risk groups to perform the weighted Kaplan-Meier estimation to the midpoint imputed data. The risk groups are defined using two risk scores derived from two working proportional hazards models with the auxiliary variables as the covariates. One is for the recurrence time and the other is for the censoring time. The method described here is explored by simulation and illustrated with an example from a colorectal polyp prevention trial.RESULTS:We first show that midpoint imputation under an assumption of independent censoring will produce an unbiased estimate of recurrence rate at the end of the trial, which is often the main interest of a colorectal polyp prevention trial, and then show in simulations that the weighted Kaplan-Meier method using the information from auxiliary variables based on the midpoint imputed data can improve efficiency in a situation with independent censoring and reduce bias in a situation with dependent censoring compared to the conventional methods, while estimating the recurrence rate at the end of the trial.CONCLUSION:The research in this paper uses midpoint imputation to handle interval-censored observations and then uses the information from auxiliary variables to adjust for dependent censoring by incorporating them into the weighted Kaplan-Meier estimation. This approach can handle a situation with multiple auxiliary variables by deriving two risk scores from two working PH models. Although the idea of this approach might appear simple, the results do show that the weighted Kaplan-Meier approach can gain efficiency and reduce bias due to dependent censoring.
EISSN:
1471-2288
DOI:
10.1186/1471-2288-9-66
Version:
Final published version
Additional Links:
http://www.biomedcentral.com/1471-2288/9/66

Full metadata record

DC FieldValue Language
dc.contributor.authorHsu, Chiu-Hsiehen
dc.contributor.authorLong, Qien
dc.contributor.authorAlberts, Daviden
dc.date.accessioned2016-05-20T08:57:16Z-
dc.date.available2016-05-20T08:57:16Z-
dc.date.issued2009en
dc.identifier.citationBMC Medical Research Methodology 2009, 9:66 doi:10.1186/1471-2288-9-66en
dc.identifier.doi10.1186/1471-2288-9-66en
dc.identifier.urihttp://hdl.handle.net/10150/610044-
dc.description.abstractBACKGROUND:Due to early colonoscopy for some participants, interval-censored observations can be introduced into the data of a colorectal polyp prevention trial. The censoring could be dependent of risk of recurrence if the reasons of having early colonoscopy are associated with recurrence. This can complicate estimation of the recurrence rate.METHODS:We propose to use midpoint imputation to convert interval-censored data problems to right censored data problems. To adjust for potential dependent censoring, we use information from auxiliary variables to define risk groups to perform the weighted Kaplan-Meier estimation to the midpoint imputed data. The risk groups are defined using two risk scores derived from two working proportional hazards models with the auxiliary variables as the covariates. One is for the recurrence time and the other is for the censoring time. The method described here is explored by simulation and illustrated with an example from a colorectal polyp prevention trial.RESULTS:We first show that midpoint imputation under an assumption of independent censoring will produce an unbiased estimate of recurrence rate at the end of the trial, which is often the main interest of a colorectal polyp prevention trial, and then show in simulations that the weighted Kaplan-Meier method using the information from auxiliary variables based on the midpoint imputed data can improve efficiency in a situation with independent censoring and reduce bias in a situation with dependent censoring compared to the conventional methods, while estimating the recurrence rate at the end of the trial.CONCLUSION:The research in this paper uses midpoint imputation to handle interval-censored observations and then uses the information from auxiliary variables to adjust for dependent censoring by incorporating them into the weighted Kaplan-Meier estimation. This approach can handle a situation with multiple auxiliary variables by deriving two risk scores from two working PH models. Although the idea of this approach might appear simple, the results do show that the weighted Kaplan-Meier approach can gain efficiency and reduce bias due to dependent censoring.en
dc.language.isoenen
dc.publisherBioMed Centralen
dc.relation.urlhttp://www.biomedcentral.com/1471-2288/9/66en
dc.rights© 2009 Hsu et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0)en
dc.titleEstimation of colorectal adenoma recurrence with dependent censoringen
dc.typeArticleen
dc.identifier.eissn1471-2288en
dc.contributor.departmentDivision of Epidemiology and Biostatistics, College of Public Health, University of Arizona, Tucson, AZ, 85724, USAen
dc.contributor.departmentArizona Cancer Center, College of Medicine, University of Arizona, Tucson, AZ, 85724, USAen
dc.contributor.departmentDepartment of Biostatistics and Bioinformatics, School of Public Health, Emory University, Atlanta, GA, 48109, USAen
dc.identifier.journalBMC Medical Research Methodologyen
dc.description.collectioninformationThis item is part of the UA Faculty Publications collection. For more information this item or other items in the UA Campus Repository, contact the University of Arizona Libraries at repository@u.library.arizona.edu.en
dc.eprint.versionFinal published versionen
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